Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids
The number of electric vehicles (EVs) and the size of smart grid are witnessing rapid expansion in both spatial and temporal dimensions. This requires an efficient dynamic spatio-temporal allocation strategy of charging stations (CSs). Such an allocation strategy should provide acceptable charging s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8949514/ |
| _version_ | 1818898085506449408 |
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| author | Rachad Atat Muhammad Ismail Erchin Serpedin Thomas Overbye |
| author_facet | Rachad Atat Muhammad Ismail Erchin Serpedin Thomas Overbye |
| author_sort | Rachad Atat |
| collection | DOAJ |
| description | The number of electric vehicles (EVs) and the size of smart grid are witnessing rapid expansion in both spatial and temporal dimensions. This requires an efficient dynamic spatio-temporal allocation strategy of charging stations (CSs). Such an allocation strategy should provide acceptable charging services at different deployment stages while meeting financial and technical constraints. As new CSs get allocated, distributed generation (DG) units need to be also dynamically allocated in both space and time to compensate for the increment in the loads due to the EV charging requests. Unfortunately, existing power grid models are not suitable to reflect such spatio-temporal evolution, and hence, new models need to be developed. In this paper, we propose a spatio-temporal expanding power grid model based on stochastic geometry. Using this flexible model, we perform a dynamic joint allocation of EV CSs and DG units based on a constrained Markov decision process. The proposed dynamic allocation strategy accounts for charging coordination mechanism within each CS, which in turn allows for maximal usage of deployed chargers. We validate the proposed stochastic geometry-based power grid model against IEEE 123-bus test system. Then, we present a case study for a 5-year CSs deployment plan. |
| first_indexed | 2024-12-19T19:26:28Z |
| format | Article |
| id | doaj.art-8d49b788a6594e7086b92b9168eae7d7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T19:26:28Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8d49b788a6594e7086b92b9168eae7d72022-12-21T20:08:45ZengIEEEIEEE Access2169-35362020-01-0187280729410.1109/ACCESS.2019.29638608949514Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding GridsRachad Atat0https://orcid.org/0000-0001-8075-6243Muhammad Ismail1Erchin Serpedin2Thomas Overbye3https://orcid.org/0000-0002-2382-2811Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, QatarDepartment of Computer Science, Tennessee Tech University, Cookeville, TN, USADepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USADepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USAThe number of electric vehicles (EVs) and the size of smart grid are witnessing rapid expansion in both spatial and temporal dimensions. This requires an efficient dynamic spatio-temporal allocation strategy of charging stations (CSs). Such an allocation strategy should provide acceptable charging services at different deployment stages while meeting financial and technical constraints. As new CSs get allocated, distributed generation (DG) units need to be also dynamically allocated in both space and time to compensate for the increment in the loads due to the EV charging requests. Unfortunately, existing power grid models are not suitable to reflect such spatio-temporal evolution, and hence, new models need to be developed. In this paper, we propose a spatio-temporal expanding power grid model based on stochastic geometry. Using this flexible model, we perform a dynamic joint allocation of EV CSs and DG units based on a constrained Markov decision process. The proposed dynamic allocation strategy accounts for charging coordination mechanism within each CS, which in turn allows for maximal usage of deployed chargers. We validate the proposed stochastic geometry-based power grid model against IEEE 123-bus test system. Then, we present a case study for a 5-year CSs deployment plan.https://ieeexplore.ieee.org/document/8949514/Charging stations allocationdynamic programelectric vehiclesexpanding power gridstochastic geometry modeling |
| spellingShingle | Rachad Atat Muhammad Ismail Erchin Serpedin Thomas Overbye Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids IEEE Access Charging stations allocation dynamic program electric vehicles expanding power grid stochastic geometry modeling |
| title | Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids |
| title_full | Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids |
| title_fullStr | Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids |
| title_full_unstemmed | Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids |
| title_short | Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids |
| title_sort | dynamic joint allocation of ev charging stations and dgs in spatio temporal expanding grids |
| topic | Charging stations allocation dynamic program electric vehicles expanding power grid stochastic geometry modeling |
| url | https://ieeexplore.ieee.org/document/8949514/ |
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